1 Environmental Variables

1.1 Rainfall

plot_ly(data, x = ~date, y = ~mm, type = 'bar')
## Warning: Ignoring 7813 observations

1.2 Salinity

plot_ly(data, x = ~date, y = ~Sal, type = 'scatter', mode = "line")
## Warning: Ignoring 50 observations

1.3 Air temp

plot_ly(data, x = ~date, y = ~TA, type = 'scatter', mode = "lines")

1.4 Water Table

plot_ly(data, x = ~date, y = ~Depth, type = 'scatter', mode = "lines")

1.5 NDVI

plot_ly(data, x = ~date, y = ~NDVI_camera, type = 'scatter', mode = "lines")

1.6 pH

plot_ly(data, x = ~date, y = ~pH, type = 'scatter', mode = "lines")

1.7 Soil Water Content

plot_ly(data, x = ~date, y = ~SWC, type = 'scatter', mode = "lines")

2 Comparison by Paritioning Technique

2.1 Cumulative NEE

data %>%
  group_by(Year2) %>%
  mutate(ANN_NEE = er_ANNnight + gpp_ANNnight,
         Reich_NEE = er_Reichstein + gpp_Reichstein,
         linear_NEE = er_linear + gpp_linear,
         ANN = cumsum(ANN_NEE),
         Reich = cumsum(Reich_NEE),
         linear = cumsum(linear_NEE)) %>%
  select(ANN, Reich, linear, Year2, DOY2) %>%
  pivot_longer(cols = c(ANN, Reich, linear),
               names_to = "Method",
               values_to = "cum_NEE") %>%
  drop_na() %>%
  filter(DOY2 > 1,
         Year2 != "2013-2014") %>%
  ggplot(aes(x = DOY2, y = cum_NEE, color = Year2)) +
  facet_wrap(~Method) +
  ylab("Cumulative NEE( µmol CO2 m-2 s-1)") +
  xlab("Days since April 1st") +
  geom_line() +
  theme_bw()

2.2 Cumulative ER

data %>%
  group_by(Year2) %>%
  mutate(ANN = cumsum(er_ANNnight),
         Reich = cumsum(er_Reichstein),
         linear = cumsum(er_ANNnight)) %>%
  select(ANN, Reich, linear, Year2, DOY2) %>%
  pivot_longer(cols = c(ANN, Reich, linear),
               names_to = "Method",
               values_to = "cum_ER") %>%
  drop_na() %>%
  filter(DOY2 > 1,
         Year2 != "2013-2014") %>%
  ggplot(aes(x = DOY2, y = cum_ER, color = Year2)) +
  facet_wrap(~Method) +
  ylab("Cumulative ER( µmol CO2 m-2 s-1)") +
  xlab("Days since April 1st") +
  geom_line() +
  theme_bw()

2.3 Cumulative GPP

data %>%
  group_by(Year2) %>%
  mutate(ANN = cumsum(gpp_ANNnight),
         Reich = cumsum(gpp_Reichstein),
         linear = cumsum(gpp_ANNnight)) %>%
  select(ANN, Reich, linear, Year2, DOY2) %>%
  pivot_longer(cols = c(ANN, Reich, linear),
               names_to = "Method",
               values_to = "cum_GPP") %>%
  drop_na() %>%
  filter(DOY2 > 1,
         Year2 != "2013-2014") %>%
  ggplot(aes(x = DOY2, y = cum_GPP, color = Year2)) +
  facet_wrap(~Method) +
  ylab("Cumulative GPP ( µmol CO2 m-2 s-1)") +
  xlab("Days since April 1st") +
  geom_line() +
  theme_bw()